Triple
T7004355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Junger Witt |
E162414
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Benson |
E387987
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Benson | Statement: [Paul Junger Witt, notableWork, Benson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Benson Context triple: [Paul Junger Witt, notableWork, Benson]
-
A.
Benson
Benson is a small town located in Johnston County, North Carolina, known for its rural character and community events.
-
B.
Benson
Benson is a historic village and civil parish in Oxfordshire, England, situated near the River Thames and known for its RAF station and traditional English countryside character.
-
C.
Benson
Benson is a masculine given name of English origin, traditionally meaning "son of Ben."
-
D.
Benson
chosen
Benson is an American sitcom that follows the sharp-witted butler Benson DuBois as he rises through the ranks of a chaotic state governor’s household and administration.
-
E.
Benson
Benson is a gumball machine-headed park manager and recurring authority figure in the animated television series "Regular Show."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc14037c81908bb87250ef29be50 |
completed | March 27, 2026, 7:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a3b2e9c8190b90c4eaaaea983ee |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:33 p.m.